Modified Mayo score <i>versus</i> Mayo score for evaluation of treatment efficacy in patients with ulcerative colitis: data from the tofacitinib OCTAVE program
Bibliographic record
Abstract
Objectives: The subjectivity of the Physician Global Assessment (PGA) is a limitation of the Mayo score in assessing severity of ulcerative colitis (UC). We compared treatment efficacy using endpoint definitions based on modified Mayo (mMayo) score, versus those based on Mayo score, using data from the tofacitinib OCTAVE program. Design: This post hoc analysis included data from two 8-week induction studies (OCTAVE Induction 1 and 2) and a 52-week maintenance study (OCTAVE Sustain). Methods: Remission and clinical response [with nonresponder imputation (NRI)] were assessed using mMayo (without PGA) and Mayo scores, and further stratified by prior tumor necrosis factor inhibitor (TNFi) failure status. Results: At week 8 of OCTAVE Induction 1 and 2, remission rates with placebo and tofacitinib 10 mg twice daily (BID), respectively, were 7.7% and 24.8% (mMayo) and 6.0% and 17.6% (Mayo). At week 52 of OCTAVE Sustain, remission rates with placebo, tofacitinib 5 and 10 mg BID, respectively, were 12.1%, 35.9%, and 42.1% (mMayo) and 11.1%, 34.3%, and 40.6% (Mayo). A statistically significant ( p < 0.05) treatment effect of tofacitinib versus placebo was observed for remission and clinical response at all time points, regardless of scoring definition or prior TNFi failure status. Conclusions: A significant effect of tofacitinib versus placebo was demonstrated across efficacy endpoints using mMayo score, consistent with previously reported data using Mayo score. Treatment effect sizes were generally similar regardless of scoring definition. This observation may help contextualize tofacitinib therapy outcomes with those of new UC therapies and support the use of Mayo score-based endpoints in UC clinical trials. Trail registration: ClinicalTrials.gov identifiers: NCT01465763; NCT01458951; NCT01458574.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".